Machine Understanding of Visual Data - PraktikumPh. D. Chuan Li; Univ.-Prof. Dr. Michael Wand
Course No.: 08.079.640
ContentsTopics are in line with the seminar of the same name. We will try out "Deep Learning" approaches in practice.
Experience in coding: We will experiment in practice one of the state of the arts deep learning framework (for example, Caffe/Torch/Matconvnet). For this reason you should be able to code (for example in python, Lua or matlab).
Requirements / organisational issuesTheis lab course expands on the topics of the accompanying seminar "Machine Understanding of Visual Data", which is held in the same semester. Therefore, participation in the seminar is mandatory for students taking the lab course. Exception: If your study regulation require a practical lab course related to "Modelling I" but not the seminar, we can find a suitable alternative topic in case seminar participation is not an option.
Time & Place
The lab course will be held in the semester break after the lecture period. The exact date will be fixed in consultation with the participants. Please make sure to attend the first meeting of the seminar for further details.
Semester: SoSe 2016